Evaluating the impact of agricultural extension on farms' performance in Crete: a nonneutral stochastic frontier approach

By Ariel Dinar, Giannis Karagiannis, Vangelis Tzouvelekas. 2007

144 citations recorded by the source corpus.

Subfields: Environmental Chemistry, General Agricultural and Biological Sciences, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/f11923121a6abfe0e217dc220961cf65fa0eb29e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Chemistry

1. John Mazunda
2. B. Bravo-Ureta
3. D. Solís
4. Mariam Kadzamira
5. C. Ragasa
6. William H. Greene

In General Agricultural and Biological Sciences

1. D. Solís
2. B. Bravo-Ureta
3. C. Ragasa
4. E. Nkonya
5. John Mazunda
6. John Pender
7. S. Benin
8. Mariam Kadzamira

In Management Science and Operations Research

1. B. Bravo-Ureta
2. D. Solís
3. John Mazunda
4. E. Nkonya
5. Mariam Kadzamira
6. D. Spielman
7. C. Ragasa
8. William H. Greene

Citations in the corpus

• From Best Practice to Best Fit: A Framework for Designing and Analyzing Pluralistic Agricultural Advisory Services Worldwide (2009, methodology): “Dinar et al. (2007) used production- and efficiency-based approaches to evaluate extension impact on farmers’ performance in Crete.”
• Privatization of agricultural extension services in the EU : Towards a lack of adequate knowledge for small-scale farms? (2013, background): “In the most recent studies, in which the effect of extension services within an agricultural production function is modelled, size is taken into account only as a continuous variable determining the levels of investment in extension services, among other inputs of the productive function (Dinar et a”
• Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project (2012, methodology): “A major shortcoming of the Dinar et al. (2007) paper is that selectivity bias is not addressed; therefore, the reported SPF parameter estimates and associated TE scores are likely to be biased.”
• The impact of agricultural extension services in the context of a heavily subsidized input system: The case of Malawi (2018, methodology): “…factor to explain differences in technical efficiency levels rather than as an input in the production function (for example, Kalirajan and Shand 1985; Seyoum, Battese, and Fleming 1998; Young and Deng 1999); or by using a combination of these models (see Dinar, Karagiannis, and Tzouvelekas 2007).”